Details

Jenny Bryan

Software Engineer, RStudio
Associate Professor of Statistics, University of British Columbia

“How I Thrive Doing the Unsexy Parts of the ‘Sexiest Job of the 21st Century’”

In 2009, Hal Varian, chief economist at Google, famously declared statistician to be the “sexiest job of the 21st century.” This was exciting news to people like Jenny Bryan. At the time, she was a professor in a department of statistics and one who took a special delight in all aspects of data analysis. She gradually intensified her focus on the workflows and software tools that make modern data analysis feasible and, ideally, fun. This led to her joining RStudio, where staff create open-source software and pro products around the statistical language called R. Bryan specializes in reducing the small agonies of practicing data science, like extracting usable data out of horrifying spreadsheets. She’ll talk about her odd career path, the incredible power of taking charge of data and the importance of keeping humans in the loop.

Jenny Bryan is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. One of the leading women in data science, Bryan is an expert in R, a programming language and free software environment for statistical computing and graphics. She earned a B.A. in economics and German at Yale University, then worked as a management consultant for two years. Her passion for working with data led her to pursue a PhD in biostatistics at the University of California, Berkeley. Today, she is a software engineer at RStudio, which develops free and open tools for R and enterprise-ready professional products for teams to scale and share work. Bryan specifically works on R packages and integrating them into fluid workflows. She serves on the leadership team of rOpenSci and Forwards, and is an ordinary member of the R Foundation.

Bryan is also an associate professor of statistics at the University of British Columbia. She is well-known in the R community, in part, for her teaching materials, such as Happy Git and GitHub for the useR, and R packages like Google Sheets.

About the Nelson Series

The data age has arrived. Information from website clicks, weather sensors, fitness devices, personal genomics, criminal activity and more is collected, stored and shared at a faster rate than ever before. Accompanying the surge of data is the rise of data science: the use of analytical and computational models and tools to derive meaning from data and to inform decision-making. To what extent are we more powerful or otherwise powerless amid this sea of data? The 2018 Nelson Series highlights the omnipresence of data science and its accompanying challenges.